zlacker

>>illumi+(OP)
The speech-to-text transcription is so incredibly wrong that it's almost dangerous to publish it like this.

For instance:

> at the beach view new screen for assistance there is a needle in his hand he's foaming from his mouth throwing off this item

What the officer actually said on the radio:

> He was going to Rainier Beach area. A request for assistance to approach two people with needles. <operator>: Call was from a neighbor in the area.

>>VWWHFS+9g
I don't have familiarity with speech-to-text but wouldn't it be possible to weight words based on their probability in this application to help resolve this. For example, suspect is probably a low frequency word in normal speech but very high in radio chatter.

>>MengYu+ki
Traditional Automatic Speech Recognition (ASR) systems do this, and this component is known as a Language Model (LM).

Typically you would use/train a LM for your domain or specifically for your dataset.